Core D: Biostatistics The objectives of the Biostatistics Core are to provide collaborative support for study design, data analysis, and dissemination of results for all SPORE projects, in addition to developing novel statistical methods to handle unique analysis problems, as needed. Statistical and methodological support is critical to ensure the quality of the design, conduct, analysis, and reporting of scientific trials and studies. With related experimental design and conceptual components, some of the quality control and analytic issues will be shared among the projects. By using the shared resource of the Biostatistics Core, all SPORE projects will benefit from the experience gained in each project. The Biostatistics Core investigators have extensive and complementary experience in quantitative methods for biomedical applications, including both clinical and basic science studies. They are committed to taking a direct interest in the substantive issues being investigated, to participating in regular project and program meetings, and to providing rigorous and innovative input on all quantitative matters arising in the projects. The 5 Specific Aims of the Biostatistics Core are to: 1. Provide detailed consultation for the development of all study protocols, including clinical trials. This includes study design, defining outcome variables and important covariates, developing appropriate measures and methods to obtain the relevant data necessary to properly answer the study questions, identifying appropriate statistical methods for analysis, and performing power and sample size calculations. 2. Provide biostatistical support during the conduct of the studies. This includes a synergistic relationship with the Clinical Trials Core to provide quality control and routine report generation as well as to assist in making any decisions related to protocol changes or revisions. 3. Collaborate in the interim and final statistical analyses of the study data. This includes identifying appropriate statistical methodology, statistical programming, data analysis, assisting with the interpretation of the results of analyses, and producing final reports and graphical displays suitable for presentation and publication. 4. Develop novel statistical methods to handle unique analysis problems, as needed. 5. Collaborate in the preparation of manuscripts and presentations of the results of the studies.